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Visium

Human colon

GSM9340374

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Human colon preview
print(sdata)
SpatialData object
├── Images
│     ├── 'GSM9340374_SITSF7_full_image': DataTree[cyx] (3, 3000, 3000), (3, 1500, 1500), (3, 750, 750), (3, 375, 375), (3, 187, 187)
│     ├── 'GSM9340374_SITSF7_hires_image': DataArray[cyx] (3, 2000, 2000)
│     └── 'GSM9340374_SITSF7_lowres_image': DataArray[cyx] (3, 600, 600)
├── Shapes
│     └── 'GSM9340374_SITSF7': GeoDataFrame shape: (9890, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (9890, 18085)
with coordinate systems:
    ▸ 'GSM9340374_SITSF7', with elements:
        GSM9340374_SITSF7_full_image (Images), GSM9340374_SITSF7_hires_image (Images), GSM9340374_SITSF7_lowres_image (Images), GSM9340374_SITSF7 (Shapes)
    ▸ 'GSM9340374_SITSF7_downscaled_hires', with elements:
        GSM9340374_SITSF7_hires_image (Images), GSM9340374_SITSF7 (Shapes)
    ▸ 'GSM9340374_SITSF7_downscaled_lowres', with elements:
        GSM9340374_SITSF7_lowres_image (Images), GSM9340374_SITSF7 (Shapes)
Load in Python
import lamindb as ln

db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("p2dczaEpp7jiUMaC")   # latest version

sdata = artifact.load()   # cache, then load into memory
group = artifact.open()   # stream without downloading
path  = artifact.cache()  # sync into the local cache, returns the path
Load from the CLI
# one-shot: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/p2dczaEpp7jiUMaC

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid p2dczaEpp7jiUMaC
Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog

ds = Catalog().cohort(uids=["p2dczaEpp7jiUMaC0000"])[0]
ds.elements()                 # inspect without downloading
sdata = ds.load(lazy=False)   # copy to the local cache and open

Docs: finding & loading data →

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Metadata

Technology
Visium
Organism
human
Tissue
colon
Modality
RNA
Observations
9,890
Tier
silver
Chemistry
Visium CytAssist v2
Resolution
3,000 × 3,000 px
mpp
4.296 µm/px
Size
160 MB
Sample ID
GSM9340374
License
CC BY 4.0
Published
Feb 10, 2026

Cite this dataset

doi.org/10.1038/s41467-026-71944-5 ↗
BibTeX
@article{Skoufou_Papoutsaki_2026,
  title = {Clonal biases dictate availability of colonic cancer driver mutations for transformation},
  volume = {17},
  ISSN = {2041-1723},
  url = {http://dx.doi.org/10.1038/s41467-026-71944-5},
  DOI = {10.1038/s41467-026-71944-5},
  number = {1},
  journal = {Nature Communications},
  publisher = {Springer Science and Business Media LLC},
  author = {Skoufou-Papoutsaki, Nefeli and Kemp, Richard and Adler, Sam and Marks, Kate and Girard, Anne-Claire and Mehmed, Shenay and Lourenço, Filipe C. and Moutin, Elisa B. and Ten Hoopen, Rogier and Morrissey, Edward and Winton, Douglas J. and Tourigny, David S.},
  year = {2026},
  month = Apr
}

Source: NCBI GEO ↗ · License: CC BY 4.0 ↗ · Reprocessed to SpatialData by SpatialData-DB